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The Design Document page provides a description of the algorithms, implementation and planned testing including unit, verification, validation and performance testing. Please read  Step 1.3 Performance Expectations that explains feature documentation requirements from the performance group point of view. 

Design Document

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The first table in Design Document gives overview of this document, from this info the Design Documents Overview page is automatically created.

In the overview table below 4.Equ means Equations and Algorithms, 5.Ver means Verification, 6.Perf - Performance, 7. Val - Validation

  • Equations: Document the equations that are being solved and describe algorithms
  • Verification Plans: Define tests that will be run to show that implementation is correct and robust. Involve unit tests to cover range of inputs as well as benchmarks.
  • Performance expectations: Explain the expected performance impact from this development
  • Validation Plans: Document what process-based, stand-alone component, and coupled model runs will be performed, and with what metrics will be used to assess validity

Use the symbols below (copy and paste) to indicate if the section is in progress or done or not started.

In the table below 4.Equ means Equations and Algorithms, 5.Ver means Verification, 6.Perf - Performance, 7. Val - Validation,   (tick) - completed, (warning) - in progress, (error) - not done

 

Overview table for the owner and an approver of this feature

1.Description

Improve efficiency of land spinup and offline land model simulations

2.OwnerDaniel Ricciuto
3.Created 
4.Equ(tick)
5.Ver(error)
6.Perf(error)
7.Val(error)
8.ApproverPeter Thornton, William Riley (Unlicensed)
9.Approved Date 
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Table of Contents

 

 

 

Title: Improving the efficiency of land spinup and offline model simulations

Requirements and Design

ACME Land Group

Date:   

Summary

This modification contains 2 major pieces:  1)  Modification of the accelerated decomposition for land model biogeochemistry spinup, and 2) Implementation of "coupler bypass" mode, which loads atmospheric input data directly in the land model.  For 1), acceleration factors now will include a dependence on mean annual temperature, and are directly connected to the rate constant parameters instead of hard-coded constants.  If Q10 or rate constant parameters are varied for UQ efforts, the acceleration factors will also change to maximize efficiency.  All pools with a turnover time of greater than 1 year (depending on the parameter value) will be accelerated, including litter and coarse woody debris (CWD).  Also included is accelerated dead wood mortality, in which dead coarse root and stem mortality is accelerated.  The biomass/height relationship and fire modules are also adjusted in accelerated mode for consistency.  Finally, in accelerated mode, in model years 1-20 (currently hard-coded), carbon-only mode is used (with saturated nitrogen).  This allows much faster spinup of biomass.  For 2), atmospheric data are loaded directly in the lnd_import_export subroutine rather than passed from datm to the coupler.  This option, which improves performance significantly, is implemented as a separate compset using SATM.  Stream files within the land model (ndep, fire data) are also disabled and all data are read on timestep 0 and held in system memory.  This option uses a compressed version of the atmospheric input (QIAN or CRU-NCEP), as well as slightly different interpolation routines, and will not be BFB with the DATM compsets.  Initial testing shows differences in the 1% range for most variables.  These improvements can shorten offline land model simulation times by 5-10x, and are primarily intended for model development and UQ.
Additional modifications include:  3)  Pulling out selected hard-coded model parameters to be read in from netcdf files, 4) Changes to existing python script framework for site simulations.


Requirements

Requirement: Provide more efficient accelerated decomposition (AD) for land biogeochemistry

Date last modified:  
Contributors: Daniel Ricciuto

Provide a framework to reach steady state in accelerated mode in land model (with active biogeochemistry) in a reduced amount of time (< 500 years) for any given climate, plant functional type, or choice of model parameters affecting decomposition rate.


Requirement: Provide option to bypass DATM and model coupler for offline land model simulations

Date last modified:  
Contributors: Daniel Ricciuto

Provide a framework to read in all model relevant inputs at the time of initialization, including meteorology, nitrogen deposition, aerosol deposition, fire data, and co2 concentrations.

Algorithmic Formulations

Design solution: Provide more efficient accelerated decomposition (AD) for land biogeochemistry

Date last modified:  
Contributors: Daniel Ricciuto

 

Modification 1)  if (model_year) < 20, set carbon_only mode active

Modificaiton 2)  In accelerated mode For dead croot and dead stem carbon only, accelerate mortality by a factor of 10

                         In accelerated mode, multiply dead stem/croot carbon pools by a factor of 10 for biomass calculation in fire model.

                         In accelerated mode,multiply dead stem/croot carbon pools by a factor of 10 for biomass/height relationship

Modification 3)  In accelerated mode, modify acceleration factors (af) of slow pools (> 1 year) from constants to a functional form:  af = f(k, Q10, MAT).

                         MAT = mean annual temperature, k = rate constant for decomposition (at 25C), Q10 = temperature sensitivity

                         In accelerated mode, increase vertical transport to match acceleration factors.

Design solution: Provide option to bypass DATM and model coupler for offline land model simulations

Date last modified:  
Contributors: Daniel Ricciuto

No algorithmic changes necessary.

 

Design and Implementation

Implementation: Provide more efficient accelerated decomposition (AD) for land biogeochemistry

Date last modified:  
Contributors: Daniel Ricciuto

 

The following subroutines are modified (Based on v0 code; this list will be revised on further review of both CNP and interface codes):
surfrdMod:  Read in mean annual temperature from surface dataset
CNAllocationMod:  Set carbon_only mode if model_year > 20, set carbon_only model false otherwise.
CNDecompCascadeCN(BGC)Mod:  Make spinup_vector an 8(7)-element array.  After parameters are read, set spinup_vector to max(1, 3/(k*Q10((MAT-25)/10.))
                                                where k is pool rate constant (in years) and MAT is mean annual T (deg C).  Apply these spinup vectors to the spinup_factor for decomp calculation. 
CN(C/N/P)StateType:  On enter_spinup, reduce SOM/Litter pool sizes by the spinup factor.  Same for dead stem/croot pools.
                                    On exit_spinup, multiply SOM/litter pool sizes by the spinup factor.  Same for dead stem/croot pools.
CNFireMod:  Multiply deadstemc by 10 for fuelc calculation.  Multiply dead wood biomass and decomp_pool fire fluxes (C/N/P) by acceleration factors.
CNGapMortalityMod:  Accelerate mortality by a factor of 10 in dead stem/croot pools for C/N/P.
CNSoilLittVertTranspMod:  Apply spinup_factors to all decomp pools.
CNVegStructMod:  Multiply dead stem C by spinup factor in accelerated mode (requires column level deadstemc calculation) for biomass/height calculation.

Implementation:  Provide option to bypass DATM and model coupler for offline land model simulations

Date last modified:  
Contributors: Daniel Ricciuto

The following subroutines are modified (Based on v0 code; this list will be revised on further review of both CNP and interface codes)

ccsm_driver:  Disable lnd2cpl communication if cpl_bypass option is used.  Disable writing logfile information every timestep.

lnd_comp_mct:  Disable lnd_export subroutine if cpl_bypass option is used.

atm2lndType:  Define and allocate new variables for met data, co2, c13o2, ndep, aerosol, hdm, lnfm inputs.

lnd_import_export

 

Planned Verification and Unit Testing 

Verification and Unit Testing: short-desciption-of-testing-here

Date last modified:  
Contributors: (add your name to this list if it does not appear)

 

How will XXX be tested? i.e. how will be we know when we have met requirement XXX. Will these unit tests be included in the ongoing going forward?

Planned Validation Testing 

Validation Testing: short-desciption-of-testing-here

Date last modified:
Contributors: (add your name to this list if it does not appear)

 

How will XXX be tested? What observational or other dataset will be used?  i.e. how will be we know when we have met requirement XXX. Will these unit tests be included in the ongoing going forward?

Planned Performance Testing 

Performance Testing: short-desciption-of-testing-here

Date last modified:
Contributors: (add your name to this list if it does not appear)

 

How will XXX be tested? i.e. how will be we know when we have met requirement XXX. Will these unit tests be included in the ongoing going forward?

 

 

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